Triple

T2658008
Position Surface form Disambiguated ID Type / Status
Subject Romeo + Juliet E54660 entity
Predicate musicBy P1952 FINISHED
Object Nellee Hooper E141179 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Nellee Hooper | Statement: [Romeo + Juliet, musicBy, Nellee Hooper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nellee Hooper
Context triple: [Romeo + Juliet, musicBy, Nellee Hooper]
  • A. Nellee Hooper chosen
    Nellee Hooper is a British record producer and remixer known for his influential work with artists such as U2, Björk, Massive Attack, and Madonna.
  • B. Don Mischer
    Don Mischer is an American television producer and director renowned for staging major live events and award shows, including multiple Academy Awards broadcasts.
  • C. Bill West
    Bill West was the husband of American country music singer Dottie West and was associated with her early career and personal life.
  • D. Michael Beinhorn
    Michael Beinhorn is an American record producer known for his work on influential rock and alternative albums by artists such as Soundgarden, Red Hot Chili Peppers, and Marilyn Manson.
  • E. Joel McNeely
    Joel McNeely is an American composer and conductor best known for his work on film and television scores, including numerous projects for Disney and other major studios.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ab49e028948190b97e01d73548b1d9 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd94c61a08190bdf5e1caeff3e788 completed March 7, 2026, 7:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98d535388190979a549dc2ce5f2f completed March 10, 2026, 4:06 a.m.
Created at: March 6, 2026, 9:53 p.m.